Energy management system

ABSTRACT

Feedback is received from a plurality of devices. External data is also received. Statistical patterns of the plurality of devices are determined based on the feedback. A policy is determined based on the statistical patterns, the feedback, and the external data. The policy may include a set of rules dictating the operation of each of the plurality of devices and reducing energy consumption at the plurality of devices. Control data based on the policy is transmitted to the plurality of devices. The control data may be operative to transform the operation of the plurality of devices according to the set of rules.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patentapplication Ser. No. 61/038,211 entitled “INTELLIGENT ILLUMINATION ANDENERGY MANAGEMENT SYSTEM” filed on Mar. 20, 2008, which is expresslyincorporated herein by reference. This patent application is alsorelated to and filed with U.S. patent application Ser. No. 12/408,503,now U.S. Pat. No. 8,148,854, entitled “MANAGING SSL FIXTURES OVER PLCNETWORKS,” Ser. No. 12/408,464, now U.S. Pat. No. 7,726,974, entitled “ACONDUCTIVE MAGNETIC COUPLING SYSTEM,” and Ser. No. 12/408,463, now U.S.Pat. No. 8,324,838, entitled “ILLUMINATION DEVICE AND FIXTURE,” each ofwhich was filed on Mar. 20, 2009 and is assigned to the same assignee asthis application. The aforementioned patent applications are expresslyincorporated herein, in their entirety, by reference.

TECHNICAL FIELD

The present invention relates generally to the field of energymanagement and, more particularly, to a controlling energy consumptionover multiple devices.

BACKGROUND

Conventional energy management techniques utilize electricity meters inorder to maximize energy usage. An electricity meter can display energyload for a building or other structure. If a user takes steps to reducethe energy usage, the user may be left to rely solely on the electricitymeter in order to determine whether those steps render an energysavings.

One significant drawback with electricity meters is that electricitymeters cannot provide feedback regarding the energy savings with respectto certain actions. For example, if the user decreases the thermostatduring the winter from seventy-two degrees to sixty-eight degrees, theuser has no way of determining the amount of energy savings resultingfrom decreasing the thermostat. If the user also dims several unusedlights, the user has no way of differentiating the energy savingsresulting from dimming the lights and energy savings resulting fromreducing the thermostat. In this regard, energy management techniquesrelying on the electricity meter are sub-optimal.

It is with respect to these considerations and others that thedisclosure made herein is presented.

SUMMARY

Technologies are described herein for providing an energy managementsystem. The energy management system (“EMS”) may include a centralcontroller that is operative to control and monitor a plurality ofdevices. Each of the devices is operative to provide device-levelfeedback to the central controller. The central controller may determinecontrol commands based on the feedback and other relevant data.

According to one embodiment, a method is provided herein for controllingenergy consumption across multiple devices. Feedback is received from aplurality of devices. External data is also received. Statisticalpatterns of the plurality of devices are determined based on thefeedback. A policy is determined based on the statistical patterns, thefeedback, and the external data. The policy may include a set of rulesdictating the operation of each of the plurality of devices and reducingenergy consumption at the plurality of devices. Control data based onthe policy is transmitted to the plurality of devices. The control datamay be operative to transform the operation of the plurality of devicesaccording to the set of rules.

It should be appreciated that the above-described subject matter mayalso be implemented as a computer-controlled apparatus, a computerprocess, a computing system, or as an article of manufacture such as acomputer-readable medium. These and various other features will beapparent from a reading of the following Detailed Description and areview of the associated drawings.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intendedthat this Summary be used to limit the scope of the claimed subjectmatter. Furthermore, the claimed subject matter is not limited toimplementations that solve any or all of the disadvantages noted in anypart of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a network architecture capable ofimplementing an energy management system, in accordance withembodiments;

FIG. 2 is a block diagram showing a light emitting diode implemented asa device in the network architecture of FIG. 1, in accordance withembodiments;

FIG. 3 is a block diagram showing the scalability of the centralcontroller of FIG. 1, in accordance with embodiments;

FIG. 4 is a flow diagram showing a method for controlling energyconsumption across multiple devices, in accordance with embodiments;

FIG. 5 is a flow diagram showing a method for providing energy-relatedfeedback to a central controller, in accordance with embodiments; and

FIG. 6 is a computer architecture diagram showing aspects of anillustrative computer hardware architecture for a computing systemcapable of implementing the embodiments presented herein.

DETAILED DESCRIPTION

The following detailed description is directed to technologies forproviding an energy management system. The energy management systemprovides control, energy management, monitoring, load management, andvarious other features. Although not so limited, the energy managementsystem may be implemented to manage the operation of an illuminationnetwork. The illumination network may utilize solid state lighting(“SSL”) technology, such as light emitting diodes (“LEDs”), lightemitting capacitors (“LECs”), and light emitting transistors (“LETs”).The illumination network may also utilize incandescent, fluorescent,halogen, high intensity discharge, and other suitable technologies.Although not so limited, embodiments described herein may refer to LEDs.It should be appreciated that other SSL technology, such as LECs andLETs, may be similarly utilized.

According to embodiments, the energy system includes a centralcontroller coupled to multiple devices, such as LEDs, over a network,such as a power line carrier (“PLC”) network. The PLC network mayinclude a communication bridge operative to enable communications withother computing devices via Ethernet, wireless, infrared, and the like.The central controller may transmit control data over the network tocontrol the devices. In particular, the devices may be individuallycontrolled through the control data. In addition to receiving andimplementing the control data from the central controller, the devicesmay provide various feedback, such as energy consumption, to the centralcontroller. Each device may provide individualized, device-levelfeedback to the central controller. Upon receiving the feedback from thedevices, the central controller may adjust the control data based on thefeedback and other relevant data. In this way, a continuous flow ofcontrol data and feedback may be established between the centralcontroller and the devices. This continuous flow of control data andfeedback between the central controller and the devices is referred toherein as a feedback loop.

While the subject matter described herein is presented in the generalcontext of program modules that execute in conjunction with theexecution of an operating system and application programs on a computersystem, those skilled in the art will recognize that otherimplementations may be performed in combination with other types ofprogram modules. Generally, program modules include routines, programs,components, data structures, and other types of structures that performparticular tasks or implement particular abstract data types. Moreover,those skilled in the art will appreciate that the subject matterdescribed herein may be practiced with other computer systemconfigurations, including hand-held devices, multiprocessor systems,microprocessor-based or programmable consumer electronics,minicomputers, mainframe computers, and the like.

In the following detailed description, references are made to theaccompanying drawings that form a part hereof, and which are shown byway of illustration specific embodiments or examples. Referring now tothe drawings, in which like numerals represent like elements through theseveral figures, aspects of a computing system and methodology forproviding an energy management system will be described. In particular,FIG. 1 illustrates a simplified network architecture 100 for providingan energy management system (“EMS”). The architecture 100 may begenerically referred to herein as the EMS. The architecture 100 includesa building 102 and a central controller 104 coupled to the building 102via a network 138, such as the PLC network, a local area network(“LAN”), and the Internet. If a PLC network is implemented as thenetwork 138, the PLC network may include a communication bridge thatenables communication via Ethernet, wireless, infrared, and the like.According to embodiments, the network 138 is a restricted, securenetwork that implements encryption technology. The central controller104 is further coupled to a data store 106.

The building 102 includes a first device 114A, a second device 114B, anda third device 114C (collectively referred to as devices 114 orgenerically referred to as a device 114). It should be appreciated thatthe building 102 may include any number of devices 114. The devices 114may be any electrical device capable of being controlled by the centralcontroller 104. In illustrative embodiments, the devices 114 includeLEDs or SSL technology implemented over a PLC network coupled to thecentral controller 104.

Embodiments described herein may leverage a PLC network for use with SSLand other solutions, whether known or developed in the future. The PLCnetwork may represent any number of discrete grids or sub-grids, and maybe characterized as single-phase, poly-phase (e.g., three-phase delta,three-phase wye, etc.), or the like, depending upon the type and natureof an AC/DC voltage source. In addition, the PLC network may supply anddistribute voltage having any number of different voltage classes (e.g.,alternating current (“AC”), direct current (“DC”), or any combination ofthe foregoing). The PLC network may also supply voltage at anyappropriate level, depending on the circumstances of particularimplementations. The PLC network may represent conductors and devicesinvolved with transmitting and distributing power within at least partsof such installations. The PLC network may also employ phase coupling.

Further, a variety of modulation techniques may be utilized over the PLCnetwork. Examples of such modulation techniques may include, but are notlimited to, differential code shift keying (“DCSK”), adaptive code shiftkeying (“ACSK”), frequency shift keying (“FSK”), orthogonalfrequency-division multiplexing (“OFDM”), and the like.

The PLC network may be divided into subnets or segments in which eachsubnet can be isolated from other subnets as necessary. The PLC networkmay be segmented using PLC blockers or PLC firewalls in order to preventnetwork saturation. Thus, for example, if a young child repeatedlyflickers a light switch in one segment, the other segments on the PLCnetwork can remain functionally operative.

In other embodiments, the devices 114 may include heaters, waterheaters, appliances, heating, ventilation, and air conditioning (“HVAC”)units, and the like. The devices 114 further include one or moreexternal sensors 116. The external sensors 116 may include sensorscapable of detecting external factors within the building 102. Examplesof external sensors 116 include, but are not limited to, sensors fordetecting and/or measuring temperature, light level, humidity, gas,pressure, motion, smoke, sound, and occupancy.

The building 102 is further coupled to an electricity meter 108 and arenewable energy storage 110. The electricity meter 108 may be anyconventional energy meter that is capable of measuring the amount ofelectricity utilized by the building 102. The renewable energy storage110 contains energy generated from natural resources, such as sunlight,wind, rain, geothermal heat, and the like. Examples of the renewableenergy storage 110 may include, but are not limited to, capacitors,batter banks, super capacitors, ultra capacitors, and the like. Asdescribed in greater detail below, the renewable energy contained in therenewable energy storage 110 may be utilized to offset energy costs,sold to the electricity company, and/or utilized to reduce emissionallowances.

The central controller 104 may be any suitable processor-based device,such as a server computer. The central controller 104 includes a controlmodule 130, an artificial intelligence (“AI”) module 132, a statisticalanalysis module 134, and an authentication module 136. In someembodiments, the central controller 104 is coupled to a computing cloud112. The central controller 104 may utilize the computing cloud 112 toperform at least some of the processing that is described herein withrespect to the central controller 104. For example, if the architecture100 is scaled to include multiple buildings 102 over a significantgeography, additional processing may be performed by other computingdevices, including other controllers, through the computing cloud 112.Further, the computing cloud 112 may enable the central controller 104to access remote data, such as weather data, customer traffic data, andthe like. The data store 106 includes one or more policies 124, feedbackdata 120, external data 126, and energy accounting data 128. At least aportion of the data in the data store 106, as well as additional data,may be accessed through the computing cloud 112.

According to embodiments, the control module 130 transmits control data118 to the devices 114. The control data 118 is operative to control thedevices 114. In particular, the control data 118 may include commands orinstructions operative to direct the devices 114 to perform specifiedoperations. The devices 114 may be controlled in order to reduce energyconsumption. The control data 118 may perform a variety of operations,including switching the device on and off and adjusting the amount ofvoltage. For example, if the devices 114 include LEDs, the control data118 may switch the LEDs on and off or dim the LEDs.

As described herein, LEDs may be characterized as digital devices,operable in response to output of a power converter to provide a levelof lighting or illumination as specified by the control data 118. Inexample implementations, the power converter may employ any number ofdifferent schemes to modulate input power as specified by the controldata 118, thereby resulting in a modulated output power supplied to theLEDs. For example, the power converter may employ pulse-width modulation(“PWM”), pulse-shape modulation (“PSM”), pulse-code modulation (“PCM”),bit-angle modulation (“BAM”), parallel pulse code modulation (“PPCM”),or other modulation techniques, whether known or developed in thefuture.

The control data 118 may be determined, through the central controller104, based on the policy 124. The policy 124 may include one or morerules dictating the operation of each of the devices 114. In thisregard, the control data 118 may include commands or instructions thatindividually control each of the devices 114 according to the policy124. For example, the policy 124 may specify certain conditions uponwhich the devices 114 are switched on and off or the amount of voltagethat is adjusted. As described in greater detail below, the AI module132 may generate and update the policy 124 according to a variety ofinformation, including the feedback data 120, the external data 126, andthe energy accounting data 128.

Upon receiving the control data 118, the devices 114 may perform thecommands or instructions contained in the control data 118. Thus, thedevices 114 may be switched on and off or the amount of voltage may beadjusted according to the control data 118. In addition to performingthe control data 118, the devices 114 may transmit the feedback data 120to the central controller 104, also through the network 138 (e.g., a PLCnetwork). The devices 114 may actively transmit the feedback data 120 tothe central controller 104 irrespective of input from the centralcontroller 104. In the alternative, the devices 114 may also transmitthe feedback data 120 to the central controller 104 in response to aquery from the central controller 104.

If the devices 114 comprise LEDs or other lighting nodes based on SSLtechnology, the control data 118 routed to the lighting nodes cancommand the lighting nodes to illuminate or turn off, and may alsocommand the lighting nodes to perform color mixing, to output particularcolors of light. For example, the lighting nodes may include SSLelements having red-green-blue (“RGB”) color output capabilities, andthe control signals may specify particular RGB values for particularlighting nodes. It is noted that white light may be specified in termsof RGB values. Put differently, white light may be specified as“colored” light. In addition, the color mixing functions describedherein may be performed with any suitable modulation schemes, includingbut not limited to the modulation schemes described herein.

As described in greater detail below with respect to FIG. 2, the devices114 may include one or more device-embedded sensors, which are operativeto detect and/or measure a variety of factors occurring at the devicelevel. Examples of such factors include, but are not limited to, energyconsumption and thermal output. Each of the devices 114 may include itsown device-embedded sensors. Thus, the feedback data 120 may includeindependent feedback from the first device 114A, the second device 114B,and the third device 114C.

The feedback data 120 may provide important information regarding theoperations of the devices 114 as well as whether the control data 118 issuccessful at reducing energy consumption or reducing thermal output,among other possible goals. To the extent that energy consumption orthermal output has not been reduced, the feedback data 120 may beutilized to determine the specific source of the problem. For example,if the first device 114A is unnecessarily consuming an excess amount ofenergy, the feedback provided from the device-embedded sensors withinthe first device 114A will indicate the excess energy consumption. Thislevel of granularity may be contrasted against the electricity meter108, which is capable of merely providing the energy usage for theentire building 102. A user reading the electricity meter 108 wouldgenerically know that energy consumption has increased. However, theuser would have no way of determining that the source of the increasedenergy consumption is at the first device 114A.

Upon receiving the feedback data 120, the central controller 104 maystore the feedback data 120 in the data store 106. The centralcontroller 104 may also store the external data 126 in the data store106. The external data 126 may be retrieved by the external sensors 116and transmitted over the network 138 to the central controller 104. Theexternal data 126 may also include data from sources other than theexternal sensors 116. For example, the external data 126 may includepower cost schedules, historical data, device information, andnon-controllable factors. The device information refers to conditions orrelations between the devices. For example, if one LED is switched off,a condition may indicate that certain other LEDs should be switched offas well. The non-controllable factors may include the time of day, date,season, and geography. In the case of a business environment, theexternal data 126 may further include operating hours, customer trafficdata, marketing data, marketing goals, sales statistics, sales goals,and the like.

The statistical analysis module 134 may determine various statisticalpatterns of the devices 114 based on the feedback data 120. Thestatistical patterns may indicate various usage patterns regarding whichdevices are operating, when the devices are operating, and the amount ofenergy being consumed by the devices. For example, an illustrative usagepattern may indicate that the lights of a retail store are kept on allday. Upon determining the statistical patterns of the devices 114 basedon the feedback data 120, the statistical analysis module 134 mayprovide the statistical patterns to the AI module 132.

In addition to receiving the statistical patterns from the statisticalanalysis module 134, the AI module 132 may also retrieve the feedbackdata 120 and the external data 126 from the data store 106. The AImodule 132 may then generate and/or update the policy 124 based on thestatistical patterns, the feedback data 120, and the external data 126.In particular, the AI module 132 may determine the rules dictating thecontrol of the device 114 based on the information provided by thestatistical patterns, the feedback data 120 and the external data 126.In the previous example where the statistical patterns indicate that thelights of a retail store are kept on all day, the external data 126 mayindicate that the retail store is only open from 10 AM to 9 PM. In thisregard, the AI module 132 may determine rules that switch off or dim thelights when the retail store is closed.

In another example, occupancy sensors within the building 102 may detectwhen the retail store is full of shoppers. The AI module 132 may utilizethe occupancy information provided by the occupancy sensors to determinerules that adjust the lighting of the retail store at times inaccordance with when the retail store is full of shoppers. The AI module132 may be operative to perform predictive analysis based on thestatistical patterns, the feedback data 120, and the external data 126.

In some embodiments, the AI module 132 may also generate and/or updatethe policy 124 based on the energy accounting data 128. The energyaccounting data 128 may include the energy allowances and energycredits. The energy allowances may specify the amount of energy that agiven user has been allocated. The energy credits may specify creditsoffsetting limits in the energy allowances. For example, the energycredits may account for the amount of renewable energy in the renewableenergy storage 110. The energy accounting data 128 may also includerelevant carbon credit data and carbon footprint data.

Once the AI module 132 has generated and/or updated the policy 124, theAI module 132 stores the policy 124 in the data store 106. The centralcontroller 104 may then implement the policy 124. In particular, thecontrol module 130 may generate the control data 118 based on the rulescontained in the policy 124. In some embodiments, the control module 130may periodically transmit the control data 118 to the devices 114through the network 138 (e.g., a PLC network). In other embodiments, thedevices 114 may be coupled to a user interface (not shown in FIG. 1).The user interface may be present within the building 102 or accessed ata remote location. Through the user interface, the control module 130may offer suggestions to a user based on the policy 124. In the previousexample where the statistical patterns indicate that the lights of aretail store are kept on all day, the control module 130 may offer asuggestion to turn off the lights when the retail store is closed. Thesuggestion may also include potential energy savings and information toaid the user in determining whether to accept the suggestion. Uponreceiving the suggestion through the user interface, the user may beprompted to accept or refuse the suggestion. If the suggestion isaccepted, then the control data 118 is passed to the devices 114. If thesuggestion is refused, then the control data 118 is not passed to thedevices 114.

According to the embodiments described herein, the central controller104 may generate the control data 118 based on the feedback data 120received from the devices 114. The central controller 104 may thentransmit the control data 118 to the devices 114 through the network 138(e.g., a PLC network). Upon receiving the control data 118 from thecentral controller 104, the devices 114 may implement the control datain order to manage energy consumption. Device-embedded sensors in thedevices 114 may collect the feedback data 120, and the devices 114 maytransmit the feedback data 120 to the central controller 104 alsothrough the network 138 (e.g., a PLC network). The continuous cycle ofcommunications including the control data 118 and the feedback data 120between the central controller 104 and the building 102 over the network138 (e.g., a PLC network) is referred to herein as a feedback loop 122.The feedback loop 122 enables the architecture 100 to provide control,energy management, load management, and other features described herein.

In some embodiments, the devices 114 may each contain an identificationchip (not shown in FIG. 1) that identifies the particular device. Asdescribed in greater detail below with respect to FIG. 2, theidentification chip may also include configuration data enabling acorresponding device driver to optimally operate the devices 114. Whenthe devices 114 initially attempt to communicate within the network 138,the authentication module 136 may authenticate the devices 114 based onthe data provided by the identification chip. The identification chipmay serve as a security feature that prevents unauthorized or unlicenseddevices from accessing the network 138. The identification chip may alsoserve as an anti-cloning feature that prevents unauthorized andunlicensed products from being manufactured. Once the devices 114 areauthorized, the authentication module 136 may allow the devices 114 andthe central controller 104 to communicate with each other over thenetwork 138.

In an illustrative device 114, the Media Access Control (“MAC”) addressor other suitable identifier may be hard-coded onto identificationchips, which are embedded onto the device 114 during manufacturing. Theidentification chips may utilize 128-bit encryption, for example, toencrypt the identifier. When the device 114 is connected to the network138, the identifier may be sent to the authentication module 136 forvalidation. The authentication module 136 may then issue a 128-bit keythat allows the device 114 to communicate over the network 138.

Referring now to FIG. 2, a block diagram showing an exampleimplementation of one of the devices 114 is illustrated. In particular,FIG. 2 shows a device 114 implemented as an LED bulb 202. As illustratedin FIG. 2, the device 114 includes the LED bulb 202 and a modularadapter 204. The LED bulb 202 includes an identification chip 206. Themodular adapter 204 includes an LED driver 208, a communications device210, one or more device-embedded sensors 212, and an identificationreading chip 214. An illustrative example of the LED bulb 202 is the“illumination device” described in Ser. No. 12/408,463, now U.S. Pat.No. 8,324,838, entitled “ILLUMINATION DEVICE AND FIXTURE,” which wasincorporated by reference above.

The device 114 further includes a user interface 216. The user interface216 may be utilized to display suggestions, as previously described, tothe user. The user may then choose to accept or reject the suggestions.The user interface 216 may be embodied as hardware, software, firmware,or combinations thereof. The user interface 216 may be a localimplementation available at or near the building 102. In thealternative, the user interface 216 may be a remote or handheldimplementation located away from the building 102. In this way, thedevices 114 can be controlled at remote locations. The communicationsdevice 210 enables the LED bulb 202 and the modular adapter 204 tocommunicate with the central controller 104 over the network 138. Thedevice-embedded sensors 212 may monitor energy consumption or thermalheat and transmit the resulting data to the central controller 104through the communications device 210.

The identification chip 206 may include an identifier, such as a MACaddress, that identifies the LED bulb 202. As previously described, theidentifier may be hard-coded into the identification chip 206 andencrypted. The identification chip 206 may then be embedded into the LEDbulb 202 during manufacturing, such that the identification chip 206becomes a fixed and irremovable part of the LED bulb 202. That is, theidentification chip 206 may be bonded to the LED bulb 202. Theidentifier may be verified by the authentication module 136 in order toallow access to the network 138. It should be appreciated that variouscomponents shown in the modular adapter 204, such the communicationsdevice 210 and the device-embedded sensor 212, may be placed directlywithin the device 114, the power supply, or other suitable componentscoupled to the device 114. An illustrative example of identificationchip 206 is the “identification circuit” described in Ser. No.12/408,463, now U.S. Pat. No. 8,324,838, entitled “ILLUMINATION DEVICEAND FIXTURE,” which was incorporated by reference above.

The identification chip 206 may also contain configuration data toenable the LED driver 208 to optimally drive the LED bulb 202. Forexample, the identification chip 206 may include device driver valuesfor driving the LED bulb 202 for optimal brightness. The configurationdata may include values for configuring current, modulation frequency,voltage, and heat.

The identification reading chip 214 may be operative to communicate withthe identification chip 206. The identification reading chip 214 maycommunicate with the identification chip 206 to verify that the LED bulb202 is an authorized and licensed device. For example, theidentification reading chip 214 may verify the LED bulb 202 based on theidentifier hard-coded on the identification chip 206. If theidentification reading chip 214 cannot verify the LED bulb 202 ordetermines that the LED bulb 202 is an unlicensed device, the modularadapter 204 may send a current spike to the connectors of the LED bulb202 in order to disable the LED bulb 202.

The identification reading chip 214 may also communicate with theidentification chip 206 to read the configuration data. Upon reading theconfiguration from the identification chip 206, the identificationreading chip 214 may adjust the values on the LED driver 208. In thisway, the LED driver 208 may drive the LED bulb 202 according to theconfiguration data on the identification chip 206. Once theauthentication module 136 has verified the LED bulb 202, the centralcontroller 104 may also transmit the control data 118 to control the LEDbulb 202.

Referring now to FIG. 3, a block diagram illustrating an expandedimplementation of the central controller 104. In particular, FIG. 3shows the scalability of the central controller 104. Because the devices114 can communicate over a network, such as the Internet, the centralcontroller 104 can be scaled in order to control additional devicesacross multiple buildings. In this way, the company can manage energyconsumption at various levels of granularity from a single device to anenterprise-wide system.

A first controller 104A, a second controller 104B, and a thirdcontroller 104C are coupled to a first building 102A, a second building102B, and a third building 102C, respectively. A fourth controller 104D,a fifth controller 104E, and a sixth controller 104F are coupled to afourth building 102D, a fifth building 102E, and a sixth building 102F,respectively. Each of the controllers 104A-104F may control and receivefeedback from devices operating in their respective buildings 102A-102F.

The buildings 102A-102C may be grouped as a first regional operation302A, and the buildings 102D-102F may be grouped as a second regionaloperation 302B. For example, businesses may sometimes categorizemultiple structures in a single entity, such as a region. The buildings102A-102C in the first regional operation 302A are coupled to a seventhcentral controller 104G. Further, the buildings 102D-102F in the secondregional operation 302B are coupled to an eighth central controller104H. The seventh central controller 104G and the eighth centralcontroller 104H may control and receive feedback from devices operatingin the respective regions 302A-302B.

The first regional operation 302A and the second regional operation 302Bmay be grouped as an enterprise 304. The buildings 102A-102F in theenterprise 304 are coupled to a ninth central controller 104I. The ninthcentral controller 104I may control and receive feedback from devicesoperating in the enterprise 304.

Referring now to FIGS. 4-5, additional details will be providedregarding the embodiments presented herein for the energy managementsystem. In particular, FIG. 4 is a flow diagram illustrating a methodfor controlling energy consumption across multiple devices from theperspective of the central controller 104. FIG. 5 is a flow diagramillustrating a method for providing energy-related feedback to a centralcontroller.

It should be appreciated that the logical operations described hereinare implemented (1) as a sequence of computer implemented acts orprogram modules running on a computing system and/or (2) asinterconnected machine logic circuits or circuit modules within thecomputing system. The implementation is a matter of choice dependent onthe performance and other requirements of the computing system.Accordingly, the logical operations described herein are referred tovariously as states operations, structural devices, acts, or modules.These operations, structural devices, acts, and modules may beimplemented in software, in firmware, in special purpose digital logic,and any combination thereof. It should be appreciated that more or feweroperations may be performed than shown in the figures and describedherein. These operations may also be performed in a different order thanthose described herein.

In FIG. 4, a routine 400 begins at operation 402, where the centralcontroller 104 receives the feedback data 120 from the devices 114. Thedevices 114 may actively transmit the feedback data 120 to the centralcontroller 104 irrespective of input from the central controller 104. Inthe alternative, the devices 114 may also transmit the feedback data 120to the central controller 104 in response to a query from the centralcontroller 104. The feedback data 120 may be generated bydevice-embedded sensors, such as the device-embedded sensor 212.Examples of the feedback data 120 include, but are not limited to,energy consumption and thermal output. By embedding the sensors into thedevice, the sensors can provide device-level feedback (e.g., the amountof energy consumed by a specific device) to the central controller 104.The routine 400 then proceeds to operation 404.

At operation 404, the central controller 104 also receives external data126. The external data 126 may be retrieved by the external sensors 116.Examples of external sensors 116 include, but are not limited to,sensors for detecting and/or measuring temperature, light level,humidity, gas, pressure, motion, smoke, sound, and occupancy. Theexternal data 126 may also include data from sources other than theexternal sensors 116. For example, the external data 126 may includepower cost schedules, historical data, device information, andnon-controllable factors, such as the time of day, season, andgeography. The device information may refer to conditions between thedevices. In the case of a business environment, the external data 126may further include operating hours, customer traffic data, marketingdata, marketing goals, sales statistics, sales goals, and the like. Theexternal data 126 may also include data from other devices. The routine400 then proceeds to operation 406.

At operation 406, the statistical analysis module 134 determinesstatistical patterns by analyzing the feedback. One example of astatistical pattern is a usage pattern, which may show patternsindicating which devices are operating, when the devices are operating,and the amount of energy being consumed by the devices. The statisticalanalysis module 134 may utilize any of a variety of technologies, suchas statistical analysis, predictive analysis, data mining, and the like.Upon determining the statistical patterns, the statistical analysismodule 134 may provide the statistical patterns to the AI module 132.The routine 400 then proceeds to operation 408.

At operation 408, the AI module 132 generates and/or updates the policy124 based on the statistical patterns, the feedback data 120, and theexternal data 126. The AI module 132 may utilize any of a variety oftechnologies, such as probabilistic models, neural networks, machinelearning, and the like. Through analyzing the statistical patterns, thefeedback data 120, and the external data 126, the AI module 132 cangenerate the rules contained in the policy 124. In particular, the AImodule 132 may generate rules that optimally manage energy usage inlight of the statistical patterns, the feedback data 120, and theexternal data 126. Upon generating and/or updating the AI module 132,the AI module 132 may store the policy 124 in the data store 106. Theroutine 400 then proceeds to operation 410.

At operation 410, the control module 130 generates the control data 118based on the policy 124 and transmits the control data 118 to thedevices 114 through the network 138. The control data 118 may includecommands that control each of the devices 114 individually according tothe policy 124. Once the control module 130 transmits the control data118 to the devices 114, the routine 400 may return to the operation 402where the central controller 104 receives the feedback data 120 from thedevices 114. The continuous transmission of the control data 118 and thefeedback data 120 between the central controller 104 and the devices 114forms the feedback loop 122.

In FIG. 5, a routine 500 begins at operation 502, where a device 114receives the control data 118 from the central controller 104. Forexample, the modular adapter 204 may receive the control data 118. Thecontrol data 118 may include values for setting a device driver, such asthe LED driver 208. The routine 500 then proceeds to operation 504,where modular adapter 204 sets the values of the LED driver 208according to the control data 118. In this case, the values may switchon or off or dim the LED bulb 202. The LED driver 208 operates LED bulb202 according to the newly set values. The routine 500 then proceeds tooperation 506.

At operation 506, the device-embedded sensor 212 collects the feedbackdata 120. Examples of the feedback data 120 include, but are not limitedto, energy consumption and thermal output. The routine 500 then proceedsto operation 508, where the device 114 transmits the feedback data 120to the central controller 104. The device 114 may actively transmit thefeedback data 120 to the central controller 104 irrespective of inputfrom the central controller 104. In the alternative, the device 114 maytransmit the feedback data 120 the central controller in response to aquery from the central controller 104.

Described below are five illustrative EMS scenarios and their respectivesolutions. Unlike conventional energy management techniques, the networkarchitecture 100 as previously described is capable of implementingthese solutions. The first scenario is a retail scenario, and the secondscenario is a residential scenario. The third scenario is an industrialscenario, and the fourth scenario involves hospitality and multi-familydwellings. The fifth scenario involves commercial buildings. Thesescenarios illustrate the scalability of network architecture 100. Itshould be appreciated that these examples are not intended to belimiting or mutually exclusive. For example, certain scenarios andsolutions may be applicable to both residential and retail environments.

1. Retail Example

The EMS can be used in a retail environment for monitoring energyconsumption and reducing energy overhead. The EMS may also be used as aproduct sales tool. Consider a drug store, for example. In this example,the drug store is a new construction. The owners of the drug store havedecided to incorporate EMS throughout the drug store including inoverhead lights, shelve lights, light sensors, motion sensors throughoutthe main floor space, beam relays on the main entrance, and solar panelson the roof. The store operates twenty-four hours a day with a skeletoncrew at night. Also, the store is closed most major holidays and islocated in an area with good solar saturation.

Below are some examples of logic that the EMS system can employ. Duringthe day, the EMS may utilize the external sensors 116 (e.g., motionsensors) to monitor and track the number of people entering and exitingthe store, as well as which areas of the store were most visited bypatrons. The EMS may also monitor the cost of utilities throughout theday. The EMS may also ensure that renewable energy from solar panels isused during peak cost hours. The EMS may also determine that thebenefits are not in the use of the renewable energy, but rather inselling the renewable energy back to the utility company by putting thepower back on the grid.

In an illustrative example, the manager may be running a special on hairspray, which is located at the hair spray shelf. Thus, the manager mayaccess the EMS, through the user interface 216, to control the lights onthe shelves located in the middle of the store. For example, the managermay increase lighting of the hairspray shelf by ten percent whiledimming the surrounding shelves by ten percent. In this way, the managercan draw attention to the hairspray shelf. The EMS may also includelight sensors placed throughout the store to measure ambient light andto maintain a pre-determined light level by adjusting the electricallighting. In this way, the EMS can harvest the available sunlight tosupplement the illumination system.

In further embodiments, the central controller 104 may access weatherdata and other information either natively or through the computingcloud 112. The EMS may adjust solar usage, HVAC usage, and lightingusage to account for cloud cover, increases in temperature, andavailable sunlight. Also, by monitoring the business holidays, the EMSmay also begin decreasing the amount of energy used by the HVAC leadingup to consecutive non-business days. During the off days, the EMS maycontinue in an energy saving mode. Then on the eve of the next businessday, the EMS may return the amount of energy used by the HVAC back tostandard levels.

Through the user interface 216, a suggestion may be prompted to thestore manager with respect to a store room in the drug store. Inparticular, the EMS may determine that the store room lights areconsistently left on, although store room is unoccupied eighty percentof the time. In this case, the EMS may suggest a rule to turn the lightsoff when there is no motion and a rule to turn the lights off aftertwenty minutes of use. The manager may then accept one of the two rulesor reject both rules.

2. Residential Example

In a typical residential setting, the EMS can be used to decrease energyconsumption in a number of ways. Due to the compartmentalized nature ofmost residential homes, the EMS can find wasted energy consumptionthroughout a residential dwelling. For example, lights in utility areasmay be a significant source of wasted energy consumption. The EMS canidentify closet lights that are left on, doors that are left opencausing strain on HVAC systems, and appliances (e.g., washers/dryers,water heaters, etc.) that are using more than standard or ideal energylevels.

In one potential usage scenario, the EMS may be used to track when thehome is occupied or unoccupied and to make adjustments accordingly. TheEMS-enabled water heaters may monitor peak usage over a given period oftime to establish a pattern. For example, the EMS may recognize that hotwater is typically requested between the hours of 7 am-9 am and thenagain at 10 pm. During off-peak times, the EMS may adjust the heater toconsume less energy. The EMS may also anticipate peak hours and adjustthe heater back to normal levels during those times.

As previously stated, the EMS may also have access to weather data. Inparticular, the EMS may delay or change certain actions based onpredicted weather conditions. In one example, if rain is predicted, theEMS may terminate or delay a scheduled watering of the lawn. In anotherexample, if the outside temperature is predicted to drop more thanfifteen degrees, the EMS may adjust HVAC settings to account for thechange in temperature.

3. Industrial Example

While the previous scenarios described above may be applicable tomultiple settings, some environments offer unique opportunities forlarge amounts of energy recovery. For example, industrial settings oftenhave a poor public perception with regards to energy conservation. Largemachines may be left idol while waiting for operators. Cutting powerduring idol time of even just a relatively small number of largemachines can save a significant amount of power. The EMS may identifywhich machines are consuming more power than is required to fulfilltheir function. For example, a break press machine that is on all daymay be used only once or twice a week. Upon identifying the break pressmachine, the EMS may enact policies that directly address the amount ofwasted energy by shutting power to the break press machine atappropriate times.

Because the EMS works in multiple voltage classes and across multiplepower phases, the EMS is capable of handling industrial environments.Further, because EMS is monitoring power consumption at the device or atthe power connection point, energy consumption monitoring and data isavailable to a wide range of products. In one example, conveyor beltsmay be shut down when the EMS is aware that there are no products to bemoved. In another example, high-bay lights may be dimmed when lightsensors detect that an ample supply of sunlight is available fromskylights.

4. Hospitality and Multi-Family Dwelling

Hotels and apartment complexes can benefit from property-wide energyaccounting as well. For example, the EMS can manage common lightingareas to reduce the amount of energy utilized in unoccupied areas, suchas halls, hotel rooms, meeting areas, and common dining rooms. When atenant occupies a given room, the property manager typically has no wayto monitoring the tenant's energy usage inside the room. The EMS enablesthe property manager to monitor and resolve any wasted energyconsumption by the tenant.

In an illustrative example, the EMS may inform the property manager thatroom #212 is consuming 180% more power than collected historical datafor that room. The EMS may further inform the property manager that theincrease in energy consumption results from the HVAC having been runningat 100% for more than three hours. The EMS can report that the room isoccupied and that a window has been left open. The EMS can then presentthe manager, through the user interface 216, with an option to decreaseHVAC performance when a window has been detected as being open and whenthe HVAC is in operation. The user interface 216 may be configured witha simple dialogue and user-friendly prompts such that no advanceprogramming knowledge is required or necessary.

5. Commercial Buildings

As used herein, daylight harvesting is a term used to describe a systemthat maintains constant lighting levels based on available naturallight. In commercial buildings, the EMS can be used for this purpose bydecreasing overhead light levels when natural sunlight has been measuredand is deemed an effective supplement to electrical light. In furtherenergy recovery techniques, the EMS may make suggestions to the userbased on building occupancy and predicted use.

One significant factor in an effective large scale deployment is thestorage of power. With a low voltage general illumination system such asLED, power can be stored in battery banks when power costs are low, andutilized when power costs are high. This technique can also be appliedto renewable energy sources such as solar and roof-mounted wind powergenerators. Further, because EMS controls load on the device level,granular control of cubical power can be associated with buildingsecurity. For example, if an employee is not logged as being onsite, thepower utilized at the employee's cubicle can be toggled, and lights usedto illuminate an employee's section can be turned off.

Referring now to FIG. 6, an exemplary computer architecture diagramshowing aspects of a computer 600 is illustrated. Examples of thecomputer 600 may include central controller 104 as well as computingdevices within the computing cloud 112. The computer 600 includes aprocessing unit 602 (“CPU”), a system memory 604, and a system bus 606that couples the memory 604 to the CPU 602. The computer 600 furtherincludes a mass storage device 612 for storing one or more programmodules 614 and one or more databases 616. Examples of the programmodules 614 include the control module 130, the AI module 132, thestatistical analysis module 134, and the authentication module 136. Anexample of the databases 616 is the data store 106. The mass storagedevice 612 is connected to the CPU 602 through a mass storage controller(not shown) connected to the bus 606. The mass storage device 612 andits associated computer-readable media provide non-volatile storage forthe computer 600. Although the description of computer-readable mediacontained herein refers to a mass storage device, such as a hard disk orCD-ROM drive, it should be appreciated by those skilled in the art thatcomputer-readable media can be any available computer storage media thatcan be accessed by the computer 600.

By way of example, and not limitation, computer-readable media mayinclude volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage of information suchas computer-readable instructions, data structures, program modules, orother data. For example, computer-readable media includes, but is notlimited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid statememory technology, CD-ROM, digital versatile disks (“DVD”), HD-DVD,BLU-RAY, or other optical storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by the computer 600.

According to various embodiments, the computer 600 may operate in anetworked environment using logical connections to remote computersthrough a network, such as the network 138. The computer 600 may connectto the network 138 through a network interface unit 610 connected to thebus 606. It should be appreciated that the network interface unit 610may also be utilized to connect to other types of networks and remotecomputer systems. The computer 600 may also include an input/outputcontroller 608 for receiving and processing input from a number of inputdevices (not shown), including a keyboard, a mouse, a microphone, and agame controller. Similarly, the input/output controller 608 may provideoutput to a display or other type of output device (not shown).

Based on the foregoing, it should be appreciated that technologies forproviding an energy management system are presented herein. Although thesubject matter presented herein has been described in language specificto computer structural features, methodological acts, and computerreadable media, it is to be understood that the invention defined in theappended claims is not necessarily limited to the specific features,acts, or media described herein. Rather, the specific features, acts andmediums are disclosed as example forms of implementing the claims.

The subject matter described above is provided by way of illustrationonly and should not be construed as limiting. Various modifications andchanges may be made to the subject matter described herein withoutfollowing the example embodiments and applications illustrated anddescribed, and without departing from the true spirit and scope of thepresent invention, which is set forth in the following claims.

What is claimed is:
 1. A processor-implemented method for controllingenergy consumption across a plurality of devices, theprocessor-implemented method comprising processor-implemented operationsfor: receiving feedback data from the plurality of devices comprisingenergy consumption data associated with the operation of at least one ofthe plurality of devices; receiving external data comprisingdevice-independent data from an external sensor; determining statisticalpatterns of the plurality of devices based at least in part on thefeedback data; determining a policy to reduce excess energy consumptionbased on the statistical patterns, and the external data, the policycomprising a set of rules dictating the operation of each of theplurality of devices and reducing energy consumption at the plurality ofdevices; providing a suggestion comprising the determined policy and anoption whether to accept or reject the suggestion through a userinterface; upon providing the suggestion and the option through the userinterface, receiving a response to accept the suggestion; and uponreceiving the response to accept the suggestion, transmitting controldata based on the policy to the plurality of devices, the control dataoperative to transform the operation of the plurality of devicesaccording to the set of rules to reduce excess energy consumption. 2.The processor-implemented method of claim 1, wherein the plurality ofdevices comprise light emitting diodes.
 3. The processor-implementedmethod of claim 1, wherein the set of rules dictating the operation ofeach of the plurality of devices and reducing energy consumption at theplurality of devices comprises a set of rules dictating whether each ofthe plurality of devices is switched on, switched off, or dimmed.
 4. Theprocessor-implemented method of claim 1, wherein the plurality devicesare implemented over a power line carrier (PLC) network.
 5. Theprocessor-implemented method of claim 1, wherein the feedback datacomprises feedback data from a device-embedded sensor; and wherein thefeedback data from the device-embedded sensor further comprises thermaloutput data.
 6. The processor-implemented method of claim 1, wherein thedevice-independent data from the external sensor comprises data of atleast one of temperature, light level, humidity, gas, pressure, motion,smoke, sound, or occupancy.
 7. The processor-implemented method of claim1, wherein the external data comprises at least one of historical usagedata, power cost schedule, non-controllable factors, device information,and carbon credit data.
 8. The processor-implemented method of claim 7,wherein the non-controllable factors comprise time of day, date, season,and geography.
 9. The processor-implemented method of claim 7, whereinthe carbon credit data comprises a carbon credit policy specifying acarbon emissions limit above which a penalty is enforced and a carbonfootprint.
 10. A non-transitory computer-readable medium havingcomputer-executable instructions stored thereupon which, when executedby a computer, cause the computer to: receive feedback data from aplurality of light emitting diode (LED) based lighting devicesassociated with a location in a retail store, wherein the feedback dataincludes sensor information and operating information associated withthe LED based lighting devices; receive external data, wherein theexternal data relates to a product offered for sale in the retail storeilluminated by the LED based lighting devices; determine statisticalpatterns of the plurality of devices based at least in part on thefeedback; determine a policy to increase sales of the product associatedwith the location based at least in part on the statistical patterns andthe external data, the policy comprising a set of rules dictating theoperation of the plurality of LED based lighting devices; provide asuggestion comprising the determined policy, wherein the determinedpolicy includes an amount of increase of lighting in the location or anamount of reduction of lighting adjacent the location, and an optionwhether to accept or reject the suggestion through a user interface;upon providing the suggestion and the option through the user interface,receive a response to accept the suggestion; and upon receiving theresponse to accept the suggestion, transmit control data based on thepolicy to the plurality of LED based lighting devices, the control dataoperative to transform the operation of the plurality of devicesaccording to the set of rules.
 11. The computer-readable medium of claim10, wherein the plurality of devices comprise light emitting diodes. 12.The computer-readable medium of claim 11, wherein the set of rulesdictating the operation of each of the plurality of devices and reducingenergy consumption at the plurality of devices comprises a set of rulesdictating whether each of the plurality of devices is switched on,switched off, or dimmed.
 13. The computer-readable medium of claim 12,wherein the plurality devices are implemented over a power line carrier(PLC) network.
 14. The computer-readable medium of claim 13, wherein thefeedback data comprises feedback data from a device-embedded sensor, andwherein the feedback data from the device-embedded sensor comprises atleast one of energy consumption data or thermal output data.
 15. Thecomputer-readable medium of claim 14, wherein the external datacomprises device-independent data from an external sensor, and whereinthe device-independent data from the external sensor comprises data ofat least one of temperature, light level, humidity, gas, pressure,motion, smoke, sound, or occupancy.
 16. An apparatus for controllingenergy consumption across a plurality of devices, the apparatuscomprising: a processor; and a computer-readable medium storinginstructions which, when executed on the processor, cause the processorto receive feedback data from a plurality of devices, receive externaldata comprising device-independent data from an external sensor,determine statistical patterns of the plurality of devices based on thefeedback data to reduce an amount of wasted energy consumption,determine a policy to reduce excess energy consumption based on thestatistical patterns, and the external data, the policy comprising a setof rules dictating the operation of each of the plurality of devices andreducing energy consumption at the plurality of devices, provide asuggestion comprising the determined policy and an option whether toaccept or reject the suggestion through a user interface, upon providingthe suggestion and the option through the user interface, receive aresponse to accept the suggestion, and upon receiving the response toaccept the suggestion, transmit control data based on the policy to theplurality of devices, the control data operative to transform theoperation of the plurality of devices according to the set of rules. 17.The apparatus of claim 16, wherein the plurality of devices compriselight emitting diodes.
 18. The apparatus of claim 17, wherein the set ofrules dictating the operation of each of the plurality of devices andreducing energy consumption at the plurality of devices comprises a setof rules dictating whether each of the plurality of devices is switchedon, switched off, or dimmed.
 19. The apparatus of claim 18, wherein theplurality devices are implemented over a power line carrier (PLC)network.
 20. The apparatus of claim 19, wherein the feedback datacomprises feedback data from a device-embedded sensor, and wherein thefeedback data from the device-embedded sensor comprises at least one ofenergy consumption or thermal output.